This invention relates generally to decision analysis systems and methods and more particularly to decision analysis systems and methods used for evaluating patient candidacy for a therapeutic procedure. The invention also relates to a method for generating a scoring system to predict a probability of death of a patient within a predetermined period of time.
As is known in the art, patient selection for a therapeutic procedure or facility which may have only limited availability is a difficult task for a physician or health care unit. One system which has been used to assist the physician in assessing the outcome and quality of care in intensive care units (ICUs) is the so-called xe2x80x9cAcute Physiology, Age, Chronic Health Evaluation (APACHE) scoring system. See for example, the article entitled xe2x80x9cInterobserver variability in the use of APACHE II scoresxe2x80x9d, by Polderman, et al., published in THE LANCET, vol. 353, Jan. 30, 1999, page 380. The APACHE scoring system has also been used in predicting deaths among intensive care unit patients, see xe2x80x9cPredicting deaths among intensive care unit patientsxe2x80x9d by Chang et al. CRITICAL CARE MEDICIAN 1998. Other scoring systems have been used, for example, in predicting morbidity and mortality risk after coronary artery bypass grating, see for example, xe2x80x9cICU Admission Score for Predicting Morbidity and Mortality Risk After Coronary Artery Bypass Graftingxe2x80x9d by Higgins et al., The Society of Thoracic Surgeons. 1997 and in predicting patient success after implantation of a Left Ventricle Assist Device (LVAD), see xe2x80x9cScreening Scale Predicts Patient Successfully Receiving Long-Term Implantable Left Ventricular Assist Devicesxe2x80x9d, by Oz et al., Supplement II, Circulation, Vol. 92, No. 9. Nov. 1, 1995.
With such scoring systems, a plurality of medical data elements are used to obtain the score. However, all of such elements are required to obtain a valid predictability result. Therefore, such scoring systems are not useful during a life-threatening decision, such as where heart replacement procedure is under consideration, because all of the required medical elements may not be available.
In accordance with the invention, a decision analysis method for evaluating patient candidacy for a therapeutic procedure is provided. The method includes predicting, in accordance with a predetermined quantitative predicative scoring system, the probability of an adverse effect on such patient absent such procedure where less than all of the medical data elements used in such scoring system may be available.
In one embodiment, the method is used to predict a probability of death of a patient within a predetermined period of time. The method includes predicting, in accordance with a predetermined quantitative predicative scoring system, the probability of death for such patient within the predetermined period of time from medical data elements of the patient where less than all of such medical data elements may be available. Thus, such method is useful for selection of a candidate during a life-threatening interval or moment when all of the medical data elements used in the scoring system might not be available.
In accordance with one embodiment, a decision analysis method for evaluating patient candidacy for a therapeutic procedure is provided. The method includes generating a point total within each of a plurality of groups. Each one of the groups has different ones of a plurality of medical data elements. The method includes determining whether the point total generated for each one of the groups exceeds a predetermined total group threshold. From such determination, the method includes predicting the probability of an adverse effect on such patient absent such procedure.
In accordance with another embodiment of the invention, a method is provided for generating a scoring system to predict a probability of death of a patient within a predetermined period of time. The method includes obtaining medical information comprising a plurality of medical data elements from each one of a plurality of patients. The information includes only those data elements available during a predetermined period of time after such one of the patients has been admitted to a critical care unit. A significance value is determined for each of the medical data elements, such value providing an indication of the significance of such medical data elements on any one of the patients dying within the predetermined period of time. From the determined significance values, a plurality of groups of the medical data elements is established with the medical data elements in each one of the groups having significance values within a corresponding predetermined significance value range. Each medical data element is dichotomized with a corresponding inclusion/exclusion threshold level. A point value is assigned to each one of such dichotomized medical data elements. For each one of the patients, a total of the point values is determined for each one of the groups including in such total only the medical elements determined by the dichotomization to be included within such total. A group threshold level is established for each one of the groups. A binary output is produced for each one of the groups in accordance with a comparison between the total of the points determined for such one of the groups and the corresponding group threshold. The binary outputs from the plurality of groups are processed to provide a score corresponding to each one of the binary outputs, such score indicating a probability of death with the predetermined period of time.